HUPO Brain Proteome Project: summary of the pilot phase and introduction of a comprehensive data reprocessing strategy

The Human Proteome Organisation (HUPO) initiated several projects focusing on the proteome analysis of distinct human organs. The Brain Proteome Project (BPP) is the initiative dedicated to the brain, its development and correlated diseases. Two pilot studies have been performed aiming at the comparison of techniques, laboratories and approaches. With the help of the results gained, objective data submission, storage and reprocessing workflow have been established. The biological relevance of the data will be drawn from the inter-laboratory comparisons as well as from the re-calculation of all data sets submitted by the different groups. In the following, results of the single groups as well as the centralised reprocessing effort will be summarised and compared, showing the added value of this concerted work

Age-related proteome analysis of the mouse brain: a 2-DE study

2-DE remains the most popular and versatile protein separation method among a rapidly growing array of various proteomics technologies. However, variability in sample processing, experimental design and data analyses results in a limited cross-validation between studies performed in different laboratories. One of the goals of the Human Proteome Organization (HUPO) is to establish standards and guidelines for proteomics studies. We contributed to the HUPO Brain Proteome Project by analyzing brains from neonatal and adult mice using 2-DE. Here we propose a standard workflow to analyze 2-DE images and extract statistically significant differences. After differential analysis and identification by MALDI-TOF/TOF, dihydropyrimidinase-related proteins, brain FABP, stathmin, isocitrate dehydrogenase, gamma enolase, annexin V, glutamine synthetase, creatine kinase B chain, triosephosphate dehydrogenase, and malate dehydrogenase were found differentially expressed between the two groups. The functions and potential mechanisms underlying the variation observed for these proteins are discussed

Truncated cystatin C in cerebrospiral fluid: Technical [corrected] artefact or biological process?

Cystatin C, a low molecular weight cysteine proteinase inhibitor present in human body fluids at physiological concentrations, is more expressed in cerebrospinal fluid (CSF) than in plasma. Mass spectrometric characterization showed that after 3 months of storage of human CSF at -20 degrees C, cystatin C was cleaved in the peptide bond between R8 and L9 and lost its eight N-termini amino acids, whereas this cleavage did not occur when stored at -80 degrees C. This truncation occurred in all CSF samples studied irrespective of the underlying neurological status, indicating a storage-related artefact rather than a physiological or pathological processing of the protein. These results stress the importance of optimal preanalytical storage conditions of any sample prior to proteomics studies

Mining mass spectra for diagnosis and biomarker discovery of cerebral accidents

In this paper we try to identify potential biomarkers for early stroke diagnosis using surface-enhanced laser desorption/ionization mass spectrometry coupled with analysis tools from machine learning and data mining. Data consist of 42 specimen samples, i.e., mass spectra divided in two big categories, stroke and control specimens. Among the stroke specimens two further categories exist that correspond to ischemic and hemorrhagic stroke; in this paper we limit our data analysis to discriminating between control and stroke specimens. We performed two suites of experiments. In the first one we simply applied a number of different machine learning algorithms; in the second one we have chosen the best performing algorithm as it was determined from the first phase and coupled it with a number of different feature selection methods. The reason for this was 2-fold, first to establish whether feature selection can indeed improve performance, which in our case it did not seem to confirm, but more importantly to acquire a small list of potentially interesting biomarkers. Of the different methods explored the most promising one was support vector machines which gave us high levels of sensitivity and specificity. Finally, by analyzing the models constructed by support vector machines we produced a small set of 13 features that could be used as potential biomarkers, and which exhibited good performance both in terms of sensitivity, specificity and model stability

A panel of cerebrospinal fluid potential biomarkers for the diagnosis of Alzheimer's disease

The diagnosis of Alzheimer's disease (AD), the most common form of dementia in the general population, usually relies upon the presence of typical clinical features and structural changes on brain magnetic resonance imaging. Over the last decade, a number of biological abnormalities have been reported in the cerebrospinal fluid (CSF) of AD patients, in particular altered levels of the tau protein and the 1-42 fragment of the amyloid precursor protein. These, however, have not yet proved sensitive and specific enough to be included in the diagnostic criteria for AD, leaving plenty of room for the search of novel biomarkers. The present study describes the analysis of CSF polypeptides by a protein-chip array technology called surface enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS). Using this approach, we detected statistically significant quantitative differences (p < 0.05) regarding four overexpressed and one underexpressed polypeptides in the CSF of AD patients as compared to healthy controls. Four of them were further purified by strong anionic exchange chromatography (SAX) and identified by MS analysis as cystatin C, two beta-2-microglobulin isoforms, an unknown 7.7 kDa polypeptide, and a 4.8 kDa VGF polypeptide. The combination of the five polypeptides for the diagnosis of AD allowed to classified six AD patients out of the nine included in this study and all the ten controls, which means in this small cohort that the specificity and sensitivity are 100% and 66%, respectively. This study, based on the protein-chip array technology, demonstrates the presence in the CSF of novel potential biomarkers for AD, which may be used for the diagnosis and perhaps the assessment of the severity and progression of the disease